`scipy.stats._mstats_basic:kruskal`

Signature

def kruskal(*samples)

Compute the Kruskal-Wallis H-test for independent samples

*samples : array_like: Two or more arrays with the sample measurements can be given as arguments.

statistic : float: The Kruskal-Wallis H statistic, corrected for ties
pvalue : float: The p-value for the test using the assumption that H has a chi square distribution

For more details on kruskal, see scipy.stats.kruskal.

from scipy.stats.mstats import kruskal

✓

Random samples from three different brands of batteries were tested to see how long the charge lasted. Results were as follows:

a = [6.3, 5.4, 5.7, 5.2, 5.0]
b = [6.9, 7.0, 6.1, 7.9]
c = [7.2, 6.9, 6.1, 6.5]

✓

Test the hypothesis that the distribution functions for all of the brands' durations are identical. Use 5% level of significance.

kruskal(a, b, c)

✗

KruskalResult(statistic=np.float64(7.113812154696133), pvalue=np.float64(0.028526948491942164))

The null hypothesis is rejected at the 5% level of significance because the returned p-value is less than the critical value of 5%.